The analysis of extraocular muscles’ activation is crucial for understanding eye movement patterns, providing insights into oculomotor control, and contributing to advancements in fields such as vision research, neurology, and biomedical engineering. Ten subjects went through the experiments, including normal watching, blinking, upward and downward movements of eyes, and eye movements to the left and right while their electromyogram (EMG) signals were recorded. We analyzed the complexity of recorded EMG signals using fractal theory, sample entropy, and approximate entropy (ApEn). The results showed that the techniques are able to decode the changes in the complexity of EMG signals between different eye movements. In other words, we can use these methods to study extraocular muscle activations in different conditions.

眼外肌激活的分析对于理解眼球运动模式、提供动眼神经控制的见解以及促进视觉研究、神经学和生物医学工程等领域的进步至关重要。十名受试者接受了实验，包括正常观看、眨眼、眼睛向上和向下运动以及眼球向左和向右运动，同时记录他们的肌电图 (EMG) 信号。我们使用分形理论、样本熵和近似熵 (ApEn) 分析了记录的 EMG 信号的复杂性。结果表明，该技术能够解码不同眼球运动之间肌电图信号复杂性的变化。换句话说，我们可以利用这些方法来研究不同条件下的眼外肌激活。